Research Assistant in AI

• Masters (MSc) degree in a biomedical discipline, or equivalent research experience.
• Previous programming experience in Python and/or R, and a sound understanding of statistics and data analysis.
• A careful, well-organised approach to data handling, documentation and reproducibility.
• Clear written and verbal communication, and the ability to work both independently and within a multidisciplinary team.
• Ideally, some experience of machine-learning methodology, medical image analysis, or biomedical datasets (desirable, not essential).

• Access to one of the largest and most deeply characterised HCM datasets available, combining genetics, AI-based imaging phenotypes and longitudinal outcomes.
• Dedicated mentorship from Dr Lara Curran within a multidisciplinary team spanning imaging, AI, genetics and cardiology, led by Professor Declan O'Regan.
• Strong scope for professional development.
• The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
• Grow your career: gain access to Imperial's sector-leading dedicated career support for researchers as well as opportunities for promotion and progression.
• As a member of research staff you have 10 development days to use to develop your skills and explore your career prospects.
• Sector-leading salary and remuneration package (including 43 days off a year and generous pension schemes).
• Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.

In this role, you will:

• Process, analyse and quality-control large-scale cardiac imaging data, including machine-learning derived 3D cardiac models.
• Integrate imaging, genetic, multi-omic and longitudinal clinical data into analysis-ready datasets.
• Apply and help develop statistical and machine-learning models to characterise disease heterogeneity and predict patient risk.
• Write clean, well-documented and reproducible code, contributing to shared analysis pipelines and open-source tools.
• Present your findings at group meetings and, where appropriate, external conferences, and contribute to manuscripts and reports (including for the British Heart Foundation).
• Handle sensitive patient data responsibly and in line with information-governance and ethical requirements.

We are seeking an enthusiastic Research Assistant to join the O'Regan Lab and contribute to a British Heart Foundation-funded programme investigating disease mechanisms and precision risk prediction in hypertrophic cardiomyopathy (HCM). You will work at the intersection of cardiac imaging, artificial intelligence and genetics, integrating 3D imaging with clinical and multi-omic data to help explain why HCM affects patients so differently, and to improve the identification of those most at risk.

Are you a computationally-minded scientist looking to apply artificial intelligence to help address a major clinical challenge in cardiology?